Probabilistic Record Linkage of Hospital Patients
How can you tell if a patient is the same person across all the different electronic systems used in a hospital?
Can you be confident with messy data when lives are on the line?
Medical startup Luminare faced this challenge in a hospital setting and used Clojure to save the day and make the nurses happy again.
This talk will explore the challenge of record linking: dealing with dirty data sets, the pros and cons of different solution approaches, and using the Felligi-Sunter method to create a probabilistic algorithm to match records.
Chris Oakman
Luminare
@oakmac1
Chris Oakman is a software developer, designer, and educator from Houston, TX.
He works at Luminare – a medical startup based out of the Texas Medical Center – and teaches software development at DigitalCrafts – a coding bootcamp school.
He is the author of several open source projects, including the cljs.info cheatsheet, the CLJS logo, and several Parinfer ports and editor plugins.